Alternatives to Depot's remote agent sandboxes

When you're building applications with AI coding tools like Claude Code, you need reliable development environments that don’t start from scratch every time.

Depot recently launched remote agent sandboxes that provide persistent cloud environments with Git integration and session sharing.

These sandboxes move Depot closer to the secure runtime category, but they’re designed for productivity and persistence with Claude Code rather than hardened security for untrusted workloads.

This article covers the top alternatives to Depot's remote agent sandboxes, comparing them across security isolation, persistence capabilities, language support, and production readiness.

Depot’s remote agent sandboxes are isolated container environments for running Claude Code agents in the cloud.

Each sandbox includes:

• 2 vCPUs and 4 GB RAM
• Startup times under 5 seconds
• Persistent filesystems
• Git integration for commits and pull requests

Pros

• Solves the “starting from scratch” problem in CI
• Fast startup and persistent state
• Git built-in

Cons

• Claude Code only
• Async sessions, no interactive dev
• Requires Depot UI for monitoring
• Isolated containers, suitable for Claude Code productivity but not designed as hardened runtimes for untrusted, multi-tenant workloads.

Pricing

• $0.01/minute, per-second billing
• Shuts down when agents exit
• Included on all Depot plans

In short: Depot improves developer productivity with Claude Code but isn’t built for secure, multi-tenant runtimes where untrusted code must be isolated.

Sandbox environments are crucial when:

1. Running AI-generated code from Claude Code, GitHub Copilot, or other assistants
2. Isolating user workloads in multi-tenant applications like online IDEs or bootcamps
3. Reviewing pull requests in clean, disposable environments
4. Executing untrusted code safely in coding challenges, educational tools, or SaaS platforms

The common thread: environments must stay isolated, persistent when needed, and production-ready for untrusted or AI-generated code.

If you need different capabilities beyond Depot's Claude Code focus, here are the main alternatives to consider:

Northflank runs over 2 million microVMs monthly, in production. We contribute to Kata Containers, Cloud Hypervisor, QEMU, and more. Our platform supports bring your own cloud and runs securely in your VPC, with several companies using Northflank to run untrusted, multi-tenant workloads at scale.

Key advantages over Depot:

• True production scale: Unlike Depot’s Claude Code focus, Northflank supports secure runtimes for any codegen tool, offering microVM-backed containers that combine container-like performance with VM-grade security.
• Multiple isolation technologies: Firecracker, Kata, gVisor, Cloud Hypervisor - flexibility across AWS, GCP, Azure, or bare-metal.
• Persistent and flexible: Sandboxes remain alive until terminated, unlike time-limited environments.
• Enterprise-ready: MFA, audit logs, RBAC, and compliance features built in.

Northflank's secure runtime advantage

Unlike standard containers that share the host kernel, Northflank utilizes microVM-backed isolation (Kata Containers, Cloud Hypervisor) in production, running millions of workloads monthly within Kubernetes. This ensures VM-grade security with container-grade workflows.

GitHub Codespaces provides hosted, container-based development environments tightly integrated with GitHub repositories and Dev Containers. It’s designed for consistent team environments and quick onboarding inside the GitHub ecosystem.

Strengths

• Native GitHub integration (pull requests, Actions, Codespaces devcontainers)
• Preconfigured container images and easy per-repo templates
• Smooth team onboarding and environment consistency

Limitations

• Tied to the GitHub ecosystem and a small set of regions
• Limited machine profiles; costs can add up at scale
• Container isolation rather than microVM-grade isolation, so not ideal for untrusted user code

Modal offers serverless, gVisor-isolated containers optimised for Python functions and machine learning pipelines, with fast cold starts and GPU (Graphics Processing Unit) options. It’s built around a function/runtime model rather than long-lived services.

Strengths

• Python-first developer experience with simple function deployments
• Fast startup and checkpointing features for iterative ML work
• GPU options for training/inference workflows

Limitations

• Python-only for function definitions
• Serverless model (no always-on, persistent services)
• No Bring Your Own Cloud (BYOC) / self-hosting; pricing can be opaque for complex pipelines
• gVisor containers rather than microVMs for isolation

If you're evaluating Modal for your AI workloads, check out our detailed comparison of top Modal Sandboxes alternatives for secure AI code execution, which provides a comprehensive analysis.

E2B.dev focuses on AI agent sandboxes with Firecracker microVM isolation and an SDK (Software Development Kit) geared toward agent workflows. It’s optimised for quick, programmatic environments rather than long-lived sessions.

Strengths

• Firecracker microVM isolation for agent execution
• Agent-friendly SDK and fast startup
• Purpose-built ergonomics for AI code execution

Limitations

• Short-lived sessions with limited persistence
• Less control over regions and underlying orchestration
• Not a full secure-runtime platform for multi-tenant production at scale

For a comprehensive analysis of E2B and its alternatives, read our article on the best alternatives to E2B.dev for running untrusted code in secure sandboxes.

Vercel Sandbox uses Firecracker-backed microVMs to run isolated workloads with simple integration into the Vercel ecosystem. It emphasises speed and simplicity for short tasks.

Strengths

• Fast microVM provisioning and simple SDK
• Fits neatly into existing Vercel workflows
• Good for short, isolated executions

Limitations

• Session limit (up to ~45 minutes) makes it unsuitable for persistent agents
• Limited language/runtime breadth compared to general-purpose platforms
• No Bring Your Own Cloud (BYOC); tied to Vercel infrastructure

If you're evaluating Vercel Sandbox, our comprehensive analysis of top Vercel Sandbox alternatives for secure AI code execution and sandbox environments covers the full range of options.

Depot’s new sandboxes bring persistence and Git integration to Claude Code agents, but remain container-based. That makes them useful for productivity, not secure multi-tenant workloads.

Northflank runs secure microVMs in production with enterprise features and persistent environments that maintain state across sessions, enabling AI agents and other workloads to run reliably.

• Security and isolation: Northflank provides VM-grade isolation with Kata Containers and Cloud Hypervisor. Depot uses containers.
• Production readiness: Northflank operates at proven scale with enterprise compliance.
• Flexibility: Northflank supports any language/runtime and multi-cloud deployment.
• Cost: Transparent pricing from $0.0038/hr, with GPU support and BYOC (Bring your own cloud) options.

Based on your specific needs, here's how to decide between the platforms:

Depot improves Claude Code workflows with persistence and Git integration, but it isn’t built as a secure runtime.

For production workloads where untrusted or AI-generated code must be isolated, Northflank provides hardened, persistent, enterprise-ready runtimes at scale.